During the training of question suggestion models, batches from each training task are randomly interleaved. [1]} preform a comprehensive study of using different combinations of these training tasks for system development, and conclude that the NQP task with mined conversation-alike sessions is the most effective among the four tasks. Adding the NQP task for training significantly reduces the amount of negative suggestions (i.e., suggestions that are either too specific or prequel, as described in Section REF ), produced by the resultant systems. This is expected as these negative suggestions rarely appear in the mined conversational search sessions. An online A/B test also validates the effectiveness of NQP. Table REF  shows some example suggestions produced a question suggestion selection system before and after the system is trained using the NQP task.
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